Demand & stockout forecast
Forecasts use average units sold per week from synced POS history. Example: if Pan de Sal averaged 102 pcs/week and you have 30 on hand, estimated stockout in ~2 days at current pace.
Items at risk (≤7 days)
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Fastest mover
Mineral Water
~210 pcs / week
Suggested reorder SKUs
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Expected weekly sales (by item)
“Based on past data, ~X pcs will sell per week” — used for purchasing hints.
| SKU | Product | Avg / week | On hand | Weeks of cover | Trend |
|---|
Likely to sell out soon
Sorted by estimated days until zero stock at current sales rate.
| SKU | Product | On hand | Avg / week | Days until empty | Action |
|---|
Weekly demand chart (top items)
Slow movers (30 days)
High stock, low sales — consider promos or reduced orders.
| SKU | Product | Sold (30d) | On hand | Last sold |
|---|
How this works in the real app
- Terminals push completed sales to the hub (SQLite → Neon).
- Hub aggregates qty sold per product per store over rolling 7/28 days.
avg_per_week = total_qty_28d / 4days_until_empty = on_hand / (avg_per_week / 7)- Pull updated forecasts on next sync or view live on webservice.